nvidia-nccl-cu13

NVIDIA Collective Communication Library (NCCL) Runtime

nvidia-nccl-cu13 License unclear Active v2.31.2 released 2026-08-11

Install

nvidia-nccl-cu13 on PyPI

pip

pip install nvidia-nccl-cu13

uv

uv add nvidia-nccl-cu13

poetry

poetry add nvidia-nccl-cu13

Package facts

License	not declared (unclear)
Python support	supports the current Python release (>=3)
Install friction	medium — platform-specific wheel
Runtime dependencies	none
Maintenance	actively maintained — 2 days since the last release
First released	2025-04-09
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: nvidia_nccl_cu13-2.31.2-py3-none-manylinux_2_18_aarch64.whl; nvidia_nccl_cu13-2.31.2-py3-none-manylinux_2_18_x86_64.whl

Keywords: cuda, nvidia, runtime, machine learning, deep learning

Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchNatural Language :: EnglishOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: MathematicsTopic :: Software DevelopmentTopic :: Software Development :: Libraries

About nvidia-nccl-cu13

from the package's own PyPI description — quoted content, verbatim

NCCL (pronounced "Nickel") is a stand-alone library of standard collective communication routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast, and reduce-scatter. It has been optimized to achieve high bandwidth on any platform using PCIe, NVLink, NVswitch, as well as networking using InfiniBand Verbs or TCP/IP sockets.

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AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

NCCL provides GPU collective communication primitives (all-reduce, all-gather, reduce, broadcast, reduce-scatter) optimized for high-bandwidth transfers across PCIe, NVLink, NVswitch, InfiniBand, and TCP/IP.

Medium install friction due to platform-specific wheels (x86_64 and aarch64 manylinux); package is actively maintained with a recent release (2 days old) and supports Python 3.5–3.11.

License treatment is unclear—no SPDX identifier or raw license text is available in the metadata, so users should verify licensing terms directly before deployment.

Usage

pip install nvidia-nccl-cu13==2.31.2

Requires NVIDIA GPU hardware and CUDA 13 runtime; wheels are platform-specific (x86_64 or aarch64 Linux only).

Verdict: nvidia-nccl-cu13 is an actively maintained library for GPU collective communication in distributed training, with no known vulnerabilities and broad Python version support. However, unclear licensing and platform-specific installation requirements demand careful evaluation before production use.

Needs verification

Exact license terms and any restrictions on commercial or research use
Whether CUDA 13 runtime must be pre-installed or is bundled with the wheel
How the package is actually imported and used in distributed GPU workloads

gpu collective communicationnvidia cuda collectivemulti-gpu synchronizationdistributed deep learninggpu communication librarynvlink collective operationscuda all-reduce